• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.37-43
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• 2001

New product development has been a key element fur organizational evolution. The bulk of research about new product strategy has focused solely on new product development function itself. This paper investigates cross-functional elements in new product development. More specifically, we suggest that there must exist a fit between new product strategy and value chain strategy. It means that, in order to support new product development activity, there must exist a relevant value chain strategy. We consider three types of integration - internal integration, customer integration, and supplier integration - as strategic elements of value chain strategy. For the case of new product strategy, we consider market newness and product technology unfamiliarity as strategic elements. We also consider two types of learning characteristic, i.e., \\\"fast-adaptive learning\\\" and \\\"slow-adaptive leaning\\\" as control factor. Learning characteristic represents firms organizational capability related with organizational learning. For example, fur fast-adaptive learning case, the effect of integration appears early in time. System dynamics simulation is employed to verify our research framework. The results exhibit that there must exist cross-functional relationships between value chain strategy and new product strategy in order to shorten total development time.al development time.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.3
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• pp.1-6
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• 2016

As the convergence speed of time domain adaptive algorithm on the LMS(Least Mean Square) becomes slow when eigen value distribution width is spread, So variable step size algorithm is used widely. But it needs a lot of calculation load. In this paper we consider new algorithm, which can reduce calculations and improve convergence speed, uses instantaneous absolute value of average noise signal adapting the exponential function. For the performance of proposed algorithm is tested and simulated to system generator. As the result we show the variable step size adaptive algorithm in proportion to instantaneous absolute value is more stable and efficient than others.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2634-2648
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• 2020

In this paper, an adaptive sparse singular value decomposition (ASSVD) algorithm is proposed to estimate the signal matrix when only one data matrix is observed and there is high dimensional white noise, in which we assume that the signal matrix is low-rank and has sparse singular vectors, i.e. it is a simultaneously low-rank and sparse matrix. It is a structured matrix since the non-zero entries are confined on some small blocks. The proposed algorithm estimates the singular values and vectors separable by exploring the structure of singular vectors, in which the recent developments in Random Matrix Theory known as anisotropic Marchenko-Pastur law are used. And then we prove that when the signal is strong in the sense that the signal to noise ratio is above some threshold, our estimator is consistent and outperforms over many state-of-the-art algorithms. Moreover, our estimator is adaptive to the data set and does not require the variance of the noise to be known or estimated. Numerical simulations indicate that ASSVD still works well when the signal matrix is not very sparse.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.5
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• pp.297-305
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• 2015

AFLS (Adaptive front lighting System) is being applied to improve safety in driving automotive at night. Safe embedded system for controlling head-lamp has to be tightly designed by considering safety requirement of hardware-dependent software, which is embedded in automotive ECU(Electronic Control Unit) hardware under severe environmental noise. In this paper, we propose an adaptive headlight controller with newly-designed symmetric angle sensor compensator, which is integrated with ECU-based adaptive front light system. The proposed system, on which additional backup hardware and emergency control algorithm are integrated, effectively detects abnormal situation and restore safe status of controlling the light-angle in AFLS operations by comparing result in symmetric angle sensor. The controlled angle value is traced into internal memory in runtime and will be continuously compared with the pre-defined lookup table (LUT) with symmetric angle value, which is used in normal operation. The watch-dog concept, which is based on using angle sensor and control-value tracer, enables quick response to restore safe light-controlling state by performing the backup sequence in emergency situation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.941-946
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• 2005

In this paper an active random noise control using adaptive learning rate neural networks is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased by a proportion of its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without leading to oscillation. It is expected that a cost function minimize rapidly and training time is decreased. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed, to validate the convergence properties of the adaptive learning rate Neural Networks. Control results show that adaptive learning rate Neural Networks control structure can outperform linear controllers and conventional neural network controller for the active random noise control.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.706-709
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• 2005

We study the adaptive stabilization of the Van der Pol equation. A parameter update law is designed by the immersion and invariance method, and is used in conjunction with both the feedback linearization and backstepping control laws. Simulation results show that the responses obtained in the adaptive case are very similar to the known parameter case, and the parameter estimator converges to the true value.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.177-180
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• 2008

There are many application areas of sensor networks, such as surveillance, hospital monitoring, and home network. These are dependent on the secure operation of networks, and will have serious outcome if the networks is injured. An adversary can inject false data into the network through the compromising node. Ye et al. proposed a statistical en-route filtering scheme (SEF) to detect such false data during forwarding process. In this scheme, it is important that the choice of the threshold value since it trades off security and overhead. This paper presents an adaptive threshold value determining method in the SEF using fuzzy logic. The fuzzy logic determines a security distance value by considering the situation of the network. The Sensor network is divided into several areas by the security distance value, it can each area to uses the different threshold value. The fuzzy based threshold value can reduce the energy consumption in transmitting.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.241-250
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• 2023

In this paper, when using the LMS algorithm for adaptive ultrasonic beamforming system, the effect of initial value setting on the margin of step parameters was studied. To this end, quasi-ideal beams, rotational beams with arbitrarily set beam widths were used as examples. In the numerical simulations, an arbitrary initial value(the number of sound sources fixed to any number) was set in the ultrasonic beamforming system, and the margin of the step parameter and convergence characteristics thereof were compared.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.123-126
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• 2000

In this paper, we propose new watermarking technique using weighting factor decision method in the watermark embedding step and adaptive threshold decision method in the watermark extracting step. In our method, we are determined weighting factor in simple by calculating distance between pixel coefficient and neighborhood pixel coefficients and threshold is adaptively determined by searching the minimized extract error value using histogram of difference value.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.999-1004
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• 2005

An algorithm for a hybrid controller consists of a sliding mode control part and a fuzzy logic part which ar purposely for nonlinear systems. The sliding mode part of the solution is based on "eigenvalue/vector"-type controller is used as the backstepping approach for tracking errors. The fuzzy logic part is a Mamdani fuzzy model. This is designed by applying sliding mode control (SMC) method to the dynamic model. The main objective is to keep the update dynamics in a stable region by used SMC. After that the plant behavior is presented to train procedure of adaptive neuro-fuzzy inference systems (ANFIS). ANFIS architecture is determined and the relevant formulation for the approach is given. Using the error (e) and rate of error (de), occur due to the difference between the desired output value (yd) and the actual output value (y) of the system. A dynamic adaptation law is proposed and proved the particularly chosen form of the adaptation strategy. Subsequently VSC creates a sliding mode in the plant behavior while the parameters of the controller are also in a sliding mode (stable trainer). This study considers the ANFIS structure with first order Sugeno model containing nine rules. Bell shaped membership functions with product inference rule are used at the fuzzification level. Finally the Mamdani fuzzy logic which is depends on adaptive neuro-fuzzy inference systems structure designed. At the transferable stage from ANFIS to Mamdani fuzzy model is adjusted for the membership function of the input value (e, de) and the actual output value (y) of the system could be changed to trapezoidal and triangular functions through tuning the parameters of the membership functions and rules base. These help adjust the contributions of both fuzzy control and variable structure control to the entire control value. The application example, control of a mass-damper system is considered. The simulation has been done using MATLAB. Three cases of the controller will be considered: for backstepping sliding-mode controller, for hybrid controller, and for adaptive backstepping sliding-mode controller. A numerical example is simulated to verify the performances of the proposed control strategy, and the simulation results show that the controller designed is more effective than the adaptive backstepping sliding mode controller.